VAST Challenge 2021 (Mini-Challenge 2) Part 3

R
sf
tmap
VAST Challenge
Investigating the Mini-Challenge 2 of VAST Challenge 2021: Wrapping Up
Author

Syed Ahmad Zaki

Published

July 26, 2021

City University London’s MC2 Sample Map Entry

5.5 Question 5 And Its Answers (A Continuation From Part 2)

Do you see evidence of suspicious activity? Identify 1- 10 locations where you believe the suspicious activity is occurring, and why. Please limit your response to 10 images and 500 words.

Suspicious Activities Can Be In The Following Forms:

  1. Unknown locations not found on map
  2. Gathering of two or more individuals at the same location at the same hour for extended periods
  3. Individuals frequenting unusual places at abnormal hours

5.5.1 Presence of Anonymous Locations (Shown As Black Dots On Map)

These are locations where there were multiple instances of GPS points remaining stationary for more than 10 mins. These unknown locations do not conform to known locations on the furnished map pic.

Code
tmap_mode("view")

Q5.5.1 <- tm_shape(mc2) +
  tm_raster(legend.show = FALSE) +
  # tm_rgb(mc2,                             # tm_rgb used to work in the previous tmap versions, but are now unable to render multiple bands in a single raster layer
  #        r = 1, 
  #        g = 2,
  #        b = 3,
  #        alpha = NA,
  #        saturation = 1,
  #        interpolate = TRUE,
  #        max.value = 255) +
  tm_shape(spots_median_sf %>%
           filter(Location.Type != "Unknown")) +
  tm_dots(col = "Location.Type",
          id = "Location", # Bold in group
          popup.vars = "Location Type:" == "Location.Type",
          size = 0.2) +
  tm_shape(spots_median_sf %>%
           filter(Location.Type == "Unknown")) +
  tm_dots(col = "black",
          id = "Location", # Bold in group
          popup.vars = "Location Type:" == "Location.Type",
          size = 0.2)

Q5.5.1

5.5.2 Suspicious Monitoring Of Key Officials’ Homes (by Bodrogi, Vann, Osvaldo and Mies)

Showcasing only residential points, Bodrogi (ID: 15, black line), Vann (ID: 16, blue line), Osvaldo (ID:21, purple line) and Mies (ID:24, red line) were seen patroling key executives’ houses located near the centre area. (Hover over the lines and points to see the ID and owner of each residence)

Code
tmap_mode("view")

Q5.5.2 <- tm_shape(sea_poly) +
  tm_polygons(col = "lightblue") +
tm_shape(Kronos_sf_small) +
  tm_polygons(col = "beige") +
tm_shape(Abila_st_buffer) +
  tm_polygons(col = "white") +
tm_shape(gps_path %>% filter(id == 15)) + # Extract Bodrogi's path
  tm_lines(col = "black",
           lty = 1,
           id = "RoleNName") +
tm_shape(gps_path %>% filter(id == 16)) + # Extract Vann's path
  tm_lines(col = "blue",
           lty = 1,
           id = "RoleNName") +  
tm_shape(gps_path %>% filter(id == 21)) + # Extract Osvaldo's path
  tm_lines(col = "purple",
           lty = 1,
           id = "RoleNName") +
tm_shape(gps_path %>% filter(id == 24)) + # Extract Mies's path
  tm_lines(col = "red",
           lty = 1,
           id = "RoleNName") +  
tm_shape(spots_median_sf %>%
           filter(Location.Type == "Residential")) +
  tm_dots(col = "green",
          size = 0.2)

Q5.5.2

5.5.3 Weird Off-Road Driving by Isande Borrasca

It begs the question as to the main cause of Isande’s wayward driving. Though it’s highly unlikely that he veers from side to side throughout his drive, it suggests that his GPS device is either faulty or that it has been tampered to cover his tracks. Relooking at the places he visited, there is little to suggest that he might be a risky character. But nonetheless, his wayward movements remain suspicious.

Code
tmap_mode("view")

Q5.5.3 <- tm_shape(sea_poly) +
  tm_polygons(col = "lightblue") +
tm_shape(Kronos_sf_small) +
  tm_polygons(col = "beige") +
tm_shape(Abila_st_buffer) +
  tm_polygons(col = "white") +
tm_shape(gps_path %>% filter(id == 28)) + # Extract Isande's path
  tm_lines(col = "black",
           lty = 1,
           id = "RoleNName") +
tm_shape(spots_median_sf) +
  tm_dots(col = "Location.Type",
          id = "Location", # Bold in group
          popup.vars = "Location Type:" == "Location.Type",
          size = 0.2)

Q5.5.3

5.5.4 Possible Suspicious Gathering At Kronos Capital On 18th and 19th Jan

On 18th Jan, Bodrogi (ID: 15, black line) met Nubarron (ID: 22, blue line) at Kronos Capital in the afternoon. This location was visited in the morning by Nubarron, as well as Vann (ID: 34, red line) in the evening. Herrero (ID:25, green line) was also stationary for approx. 24 hours in this location on 19th Jan.

Code
tmap_mode("view")

Q5.5.4 <- tm_shape(sea_poly) +
  tm_polygons(col = "lightblue") +
tm_shape(Kronos_sf_small) +
  tm_polygons(col = "beige") +
tm_shape(Abila_st_buffer) +
  tm_polygons(col = "white") +
tm_shape(gps_path %>% filter(id==15 & day==18)) + # Extract Bodrogi's path on 18th Jan
  tm_lines(col = "black",
           lty = 1,
           id = "RoleNName") +
tm_shape(gps_path %>% filter(id==22 & day==18)) + # Extract Nubarron's path on 18th Jan
  tm_lines(col = "blue",
           lty = 1,
           id = "RoleNName") +  
tm_shape(gps_path %>% filter(id==34 & day==18)) + # Extract Vann's path on 18th Jan
  tm_lines(col = "red",
           lty = 1,
           id = "RoleNName") +
tm_shape(gps_path %>% filter(id==25 & day==19)) + # Extract Herrero's path on 19th Jan
  tm_lines(col = "green",
           lty = 1,
           id = "RoleNName") +  
tm_shape(spots_median_sf %>%
           filter(Location == "Kronos Capital")) +
  tm_dots(col = "green",
          size = 0.2)

Q5.5.4

5.5.5 Large Gathering At Engineer Lar’s Home on Jan 10 Late Evening

A large gathering of 13 individuals, from both the IT and Geological department, was spotted in the late evening on 10th Jan.

Code
tmap_mode("view")

Q5.5.5 <- tm_shape(sea_poly) +
  tm_polygons(col = "lightblue") +
tm_shape(Kronos_sf_small) +
  tm_polygons(col = "beige") +
tm_shape(Abila_st_buffer) +
  tm_polygons(col = "white") +

# Extract a multitude of visitors to Lars' Home on Jan 10th Late Evening
tm_shape(gps_path %>% 
           filter(day==10 & id==1  |
                            id==2  |
                            id==5  |
                            id==6  |
                            id==7  |
                            id==8  |
                            id==9  |
                            id==11 |
                            id==14 |
                            id==18 |
                            id==19 |
                            id==25 |
                            id==33)) +
  tm_lines(col = "black",
           lty = 1,
           id = "RoleNName") +  
tm_shape(spots_median_sf %>%
           filter(Location == "2 Engineer Lars's Home")) +
  tm_dots(col = "green",
          size = 0.2)

Q5.5.5

5.6 Question 6 And Its Answers

If you solved this mini-challenge in 2014, how did you approach it differently this year?

5.6.1 Question Not Applicable

We did not attempt this mini-challenge in 2014.

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